Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral disclosure burden. It usefully states that matching is case-insensitive and that results are limited to 50 rows, but it does not mention default limit behavior, result ordering, empty-result behavior, or the response structure for a tool with no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, information-dense sentence with no filler. It front-loads the resource and search behavior, and every element contributes to understanding how the tool behaves.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is adequate for a simple search tool, but given the absence of annotations and output schema, it leaves gaps: no default limit, no ordering guarantee, no empty-result behavior, and no routing guidance among sibling dataset tools. It is not incomplete enough to be unusable, but it is not fully self-sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 50%, so the description is expected to compensate. It does add meaning beyond the schema: 'up to 50' clarifies the limit parameter's role, and 'case-insensitive' adds a search behavior not present in the schema. However, it does not state what happens when limit is omitted.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the operation as searching rows of the Amortlane dataset for cells containing the query, with a concrete cap of 50 results. It does not explicitly name sibling tools or contrast with them, but the behavior is specific and distinct from the listed dataset_* siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given about when to choose dataset_search over alternatives like dataset_row, dataset_top, or dataset_columns. The intended use can be inferred, but the description offers no explicit context, exclusions, or comparisons.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.